1. A Real-Time Video Multicast Architecture for Assured Forwarding Services Ashraf Matrawy, Ioannis Lambadaris IEEE TRANSACTIONS ON MULTIMEDIA, AUGUST 2005

2. Outline Introduction Network Model End-to-End architecture Rate-Adaptation algorithm Simulation Results Conclusion

3. Introduction Develop an architecture for multicast real- time MPEG4 over IP networks that provide service differentiation Deployment of IP multicast services over the Internet is not rapid –Main factor: multicast congestion control scheme is not robust as unicast

4. The challenges of multicast congestion control The heterogeneity of receivers’ networking capabilities and their QoS-requirement –Layers problem: uniform drop, all layers assumed to follow the same multicast tree Maintaining the scalability of the multicast congestion control technique is a difficult task

5. Overview of the work Develop a multicast congestion control scheme that relies on assured forwarding (AF) architecture

6. Why AF ? Help build a simple end-to-end architecture that avoids the problems of earlier approaches to multicast congestion control Not require major changes in current router’s functionality, so deployed soon in Internet routers

7. Different with IETF proposed AF service For simpler experiments, don’t completely implement the IETF proposed AF service Don’t consider marking/policing at the edge routers and instead marked the packets at the sender

8. Network model Goal: –Provide different levels of quality to receivers –Guaranteeing a minimum quality during congestion Consider IP networks that support priority- dropping as a means of providing different levels of services –AF-compliant router achieve that by active queue management (AQM) Assume that routers can provide Congestion Notification messages upstream to the sender with information about router’s congestion status

9. Queue management for AF In RFC, recommends provides 4 classes of AF and 3 drop precedence levels Implement priority-dropping in AF is based on AQM techniques AF is usually based on variants of random early detection (RED)

10. Queue management for AF The actions of RED based on We assume that AF routers support one of RED’s extensions for service differentiation, namely, RIO and WRED

11. Queue management for AF RIO –RED with In/Out bits –The number of RIO out packets can be calculated based on packets in the whole queue (RIO-C) and out packets only (RIO-D) –RIO-C more protect higher priority, RIO-D more protect lower priority WRED –Weighted RED –Use one average queue length to make dropping decisions

12. Backward Explicit Congestion Notification This paper uses BECN-style feedback from router to the flow controller of the multicast sender Send messages back to the sender based on the status of every virtual queue, used by the rate-adaptation algorithm

13. End-to-end architecture rate-adaptation alg. Congestion !!

14. Advantages of this architecture Send packets as one stream is much easier to handle than multiple streams With priority dropping, ensure that a minimum quality will be received when congestion Scalability is minimized when the feedback to the sender is provided from the routers rather than form receivers

15. The rate-adaptation algorithm is the probability that virtual queue i will generate a feedback message at time t

16. The rate-adaptation algorithm is the rate (in packets/s) of layer i at the time t

17. The rate-adaptation algorithm The constraints: Depend on –Limitation imposed by the video encoder –Outgoing link speed –Minimum accepted video quality at the receiver

18. The rate-adaptation algorithm Round-Trip Time (RTT) – will depend of the sender’s estimation of the RTT from the routers that send the feedback information Feedback Suppression –To reduce feedback, routers will send feedback with a probability instead of sending a feedback message for every packet

19. The rate-adaptation algorithm Calculation of Probabilities –The quantities and are calculated using real-time measurements from the network rather than an analytical model weight

20. The rate-adaptation algorithm Changing the Equation Parameters –At the highest priority layer, the sender selects MAX( ) received during –With the constraint, avoid the problem where a slow portion of the receivers drag the sending rate –At lower priority layers, select MIN ( ) –With constraint –Utilize receivers’ links with extra available bandwidth

21. The rate-adaptation algorithm Feedback

22. Simulation Use network simulator – ns version 2.1b8a One AF class, and two drop precedence levels Simulations are 300s =0.1 for both priority levels (i=1,2) and at the routers for these levels are the same in all experiment

23. Results – a. Basic test Goal: check how the sender will adjust its rate for the high-priority packets to closely match the bandwidth available at the receiver

24. Results – a. Basic test

25. Results – b. Heterogeneity Test Goal: test of how the architecture deal with heterogeneity

26. Results – b. Heterogeneity Test

32. Results – C. Scalability Test Goal: test how the architecture handles a larger number of receivers R1~15: 100kbps, R16~30: 200kbps, R31~45: 300kbps, R46~60: 400kbps With RIO-D

33. Results – C. Scalability Test

36. Conclusion Present an architecture and a rate- adaptation algorithm for real-time video transport in AF network Enable users with different capabilities to receive the same video multicast in different qualities

37. RED